Get AI Model

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the tool's return fields (pricing, context window, speed) but does not mention error behavior (e.g., invalid slug), authentication requirements, rate limits, or the exact output structure. For a read operation, this is minimal but not dangerously opaque.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core action ('Get a single AI model') and includes essential details (by slug, pricing, context window, speed). Every word adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 1-parameter tool with no output schema, the description covers the basic purpose and return values. However, it lacks usage guidance and behavioral caveats (e.g., what happens if the slug is not found). It is adequate but not fully complete for an AI agent making invocation decisions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (the only parameter 'slug' is described as 'Model slug'). The description confirms the filtering mechanism ('by slug') but adds no new semantic detail about the parameter beyond what the schema already provides. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get a single AI model by slug' with specific return fields (pricing, context window, speed). This distinctly differentiates it from sibling tools like list_ai_models, which likely retrieves multiple models.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you have a specific slug and need details for one model, but it does not explicitly state when to prefer this over list_ai_models or other siblings. No exclusion or alternative guidance is provided beyond the implicit 'single' vs 'list' contrast.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.